The Competitiveness Agenda

October 7, 2014

This research article is Chapter 3 in the report, "The Future of Data-Driven Innovation."


Read and download this article in PDF format. 


By John Raidt

In The Adventure of the Copper Beeches,” Sherlock Holmes exclaims, “Data! Data! Data!…I can't make bricks without clay.”[1]

Big Data is enabling the U.S. business system to produce revolutionary bricks from exotic new clay that can transform the nation’s global economic competitiveness; that is, America’s capacity to stimulate investment and create high-quality jobs.   

The opportunity could not be timelier. While the forces of globalization are opening vast new consumer markets to our goods, services, and solutions, we face intensifying international competition to be the supplier of choice. Warns the Council on Competitiveness, America must “innovate or abdicate” its global economic leadership.[2]



Though America did not discover date-driven innovation—a phenomenon as old as civilization itself—we have set the standard of excellence by applying the indispensable catalysts: incentive, entrepreneurship, and freedom. A new dimension with vast possibilities, however, is fast materializing thanks to a confluence of trends—spurred by technologies pioneered mostly by American firms—that enable us to tap massive digital data flows.

From this accumulating wealth of digital clay, generated by the proliferation of information and communications technology, we are able to extract fresh insights, create novel capabilities, and shape new industries. These competitive assets can catapult the American economy to new heights of leadership and prosperity.

As Moore’s law continues to assert itself across the spectrum of information and communication technology (ICT)—from which the Internet of Everything (IoE) is emerging—data production and the ability to process it faster and more affordably will multiply at an Olympic pace. In a McKinsey Quarterly article, The Second Economy,” author Brian Arthur observes that “with the coming of the Industrial Revolution…the economy developed a muscular system in the form of machine power. Now it is developing a neural system.”[3]

What he means is that in the same way that the human body transmits information to the brain, enabling high-order human function, our industrial, economic, social, and environmental limbs now have the capacity to produce a rich stream of digital information such that manmade systems can function more cognitively and productively. 

GE estimates the gain to global GDP from this advanced system could top $15 trillion by 2030,[4] and Cisco notes that the IoE could yield a 21% growth in global corporate profits.[5] CIO reports that “if the cost savings and efficiency gains from the industrial Internet can boost U.S. productivity growth by 1 to 1.5 percentage points, the benefit in terms of economic growth could be substantial, potentially translating to a gain of 25% to 40% of current per capita GDP.”[6]

For an economy that has been idling in sub-2% GDP growth, bedeviled by stubbornly high unemployment, stagnated wages, and massive fiscal imbalances, the emergence of a powerful new catalyst for growth is providential. This is particularly true considering that the pull of capital and business operations toward growth markets abroad (mainly in Asia) is so forceful. Mastering data-driven innovation sectors, such as analytics, will enable U.S. firms to deliver a host of new high-value services to global customers via the Internet, while also harnessing the know-how we derive to compete better in every commercial field.[7]

At the enterprise level, data-driven innovation can propel businesses to new levels of productivity, profitability, and competitiveness. In a survey conducted by Oxford University and IBM, “63% of respondents reported that the use of information—including Big Data and analytics—is creating a competitive advantage for their organizations.”[8]

Those who fail to grasp the importance of this new reality are at risk. McKinsey reports, “Across sectors, we expect to see value accruing to leading users of big data at the expense of laggards, a trend for which the emerging evidence is growing stronger.”[9] The Economist puts it more starkly: “Companies that can harness big data will trample data-incompetents.”[10]

Yet, success is not self-generating. American firms must compete vigorously on the basis of capability, quality, price, and accessibility for worldwide market share in every product and service category. To compete at our best, U.S. excellence in harnessing Big Data to drive innovation across four domains is a national economic imperative.  


  • Direct Innovation: Big Data is a major industry in and of itself. The United States has an enormous competitive stake in being the leading developer of goods and services across the Big Data supply chain. 
  • Derivative Innovation: Big Data can be harnessed to produce big insight that will enable our economy to produce better goods, services, and solutions across the commercial spectrum.
  • Enterprise Management Innovation: Big Data can be employed to invent better business models and decision-making processes that make enterprises more successful.
  • Systemic Innovation: Big Data and data-driven innovation can be used to improve national economic policy and optimize the variables that produce a fertile business environment.

To best understand the advantages, opportunities, challenges, and imperatives in the Big Data age, each of these categories are discussed in depth.



In many respects, the Big Data industry is akin to energy development or mining—a broad and integrative process of producing and refining a raw material to power a broader set of economic activities. Here we examine some business components in the main links of the Big Data supply chain, each of which bears significantly on our competitive fortunes.  


Generation and Collection  

The number of people and institutions using the Internet to socialize, communicate, and shop has accumulated rapidly alongside the proliferation of communication devices, giving rise to an explosion of mobile access, online services, and electronic transactions. The amount of data being created and collected by these forces, already growing 40% per year, will continue to swell at exponential rates.[11] As a result, the race to market cheaper, faster, and better ICT equipment and services, as well as accommodate the gargantuan data flow they produce, will continue to be a hotly contested economic battle space.  

Among the fastest growing sources of data generation is sensor technology. Cheap, highly capable sensors can be imbedded in almost anything to transmit electronic data via inexpensive wireless links. The technology is proliferating at a rate of nearly 30% annually, ushering in an era of sensor ubiquity—in the environment, machines, networks, and even in the human body.[12]

BCC estimates that the worldwide sensors market was $56.3 billion in 2010, growing to $91.5 billion by 2016 and $154 billion by 2020.[13] In an article on the “Smart/Intelligent Sensor Markets,” MarketsandMarkets estimates that “the total revenue of global smart sensor market is expected to grow at an estimated CAGR of 36.25% from 2013 to 2020.”[14]

Joining sensors in revolutionizing data generation is robotics technology. Robots are capable of streaming enormous amounts of data about the functions they perform, measure, and monitor. This is a growing field with large economic potential. BCC Research reports that the global robotics industry, worth $17.3 billion in 2008, should top $22 billion this year and exceed $29 billion by 2018.[15] Amazon reports that the use of robotics could bring efficiencies, saving the company up to $900 million per year.[16] The race for leadership in supplying and servicing this high-tech, high-wage field is moving into high gear, as will the competition to reap the data-driven gains that robotic data streaming can generate.


Transmission, Storage, and Security

Regardless of how digital information is generated, without the ability to electronically transmit, store, and access it, little value can be extracted. For this reason, improving the ability of wired and wireless broadband technology to transmit electronic data is a commercial opportunity and competitive necessity for the Big Data era to fully blossom. 

As the pioneer of the Internet, the U.S. innovation system will be relied upon for the products and solutions that can keep the information superhighway untangled and operating at peak efficiency, which allows bigger datasets to move with the speed and reliability required in today’s on-demand economy. The global competition across ICT markets will remain intense, particularly as the demand for computers, mobile phones, Internet access, and broadband connections expands in rapidly growing but price-sensitive consumer markets abroad.  

There is also an enormous competitive advantage for innovators in the business of storing massive amounts of digital information so it can be aggregated, retained, and organized for analysis and use. One of the larger breakthroughs in data storage has been the advent of cloud computing. Earlier this year, Forbes reported that end-user spending on cloud services could exceed $180 billion by 2015, with a global market for cloud equipment climbing to $79.1 billion by 2018.[17]

Accessing this vast potential, however, demands information security. The Big Data era confers big responsibilities to ensure data security and integrity. Without proper security, Big Data (and by extension, data-driven innovation) will flag as data breaches and misuse undermine essential public support. Tremendous comparative advantage will be enjoyed by nations whose business systems, infrastructure and polices can provide the best security for sensitive data. Moreover, the competitive opportunity for U.S. firms to fill growing demand for data protection solutions (likely to be spurred by national and international policies, laws, and regulations) is enormous.



Earlier, we likened Big Data to a raw material, the true value of which is created in processing the resource into useful products. The refining of Big Data into insight, knowledge, and actionable information is the job of analytics. An article in The American, “The Next Great Growth Cycle,” notes that “Big Data analytics and services, non-existent just a few years ago, is already a $3 billion industry and will be $20 billion in a half-decade.”[18]

The all-too-common misperception is that Big Data analytics is about studying consumer behavior to improve marketing effectiveness. Though valuable to producers and consumers, this purpose is merely the surface of a far richer and deeper enterprise of creating data-driven insight in every domain. These include: solving scientific mysteries; identifying meaningful patterns and anomalies; discovering important connections, correlations, and causes and effects; measuring outcomes; shedding light on the dynamics and performance of complex manmade and natural systems; and helping machines learn and perform more capably. For instance:

  • Drug companies sharing anonymized clinical trial data are producing fresh insight into pharmaceutical safety and effectiveness. Massive amounts of genomic and clinical data are informing the development of better pharmaceuticals and therapies and opening promising new doors in cancer research.
  • Environmental sensors that measure complex variables are enabling data-based precision agriculture to increase farm yields, helping utilities manage energy demand and improving weather forecasting to support smoother running delivery schedules and supply chains. 
  • Machine-to-machine data flows help monitor systems (e.g., jet engines), providing operational insight, pointing to preventative maintenance requirements, and improving safety and efficiency.

Extracting knowledge from data to inform innovation and business decisions across the economy is big business. The possibilities are astronomical, bounded only by the limits of our capacity to create insight-producing software, algorithms, and computer models.




The book Moneyball chronicles the exploits of Oakland A’s President Billy Beane, who used data to pioneer cost-effective, winning baseball.[19] It was not the data that was novel but rather Beane’s ability to extract meaning and cleverly employ it. 

As a result, the A’s (a small-market team) achieved an average of 96 wins per season at an average cost of $2 million per player. Compare that to the New York Yankees’ average of 99 wins per season, which costs some $5.8 million per player.[20] Using our national pastime to model the possibilities in Big Data is appropriate but equally microscopic compared to the profound ramifications across all industries and activities. Here we take a deeper dive into some of the areas in which data-driven innovation can make U.S. industries and firms more competitive.  


Retail and Marketing

Search engines, websites, electronic transactions, and indeed, all of the 21st century data-making tools and activities generate cascades of information that data scientists can mine to understand the demographics, needs, wants, and preferences of entire markets. This enables marketers to better understand customer motives and behavior and also makes possible tailored, intelligent marketing and customized manufacturing (through data-enabled smart machines and 3D printing) that is hastening the decline of the one-size-fits-all era for many products and services.  

The McKinsey Global Institute reports that global personal data service providers generate $100 billion in revenue each year, and retailers who use these services are enjoying a 60% increase in net margins.[21] How is such data used to grow revenue and efficiency? Take, for example, Amazon, which uses a recommendation engine to promote products to targeted consumers. According to MGI, some 30% of Amazon's sales are generated by this recommendation engine.[22] Or take the example of XO Communications: after identifying factors that can suggest a customer will depart, the company improved its customer retention rate by 26%. This translated into an annual net gain of $3.8 million.[23]



The American magazine reports that computational manufacturing “is poised to become a trillion dollar industry, unleashing as big a change in how we make things as did mass production in an earlier era, and as did the agricultural revolution in how we grew things. It is a manufacturing paradigm defined not by cheap labor, but high talent.”[24]

Electronic sensors embedded in machines, from consumer goods to factory equipment, stream data to both producers and users about the equipment’s design, performance, and maintenance. Sensory data (such as vibration, pressure and voltage) can be used to improve the operational efficiency and the productivity of product design and manufacturing processes.  

For example, data generated by heavy machinery (such as aircraft engines or power plant components) can offer insight into operation, helping ensure that systems are operating at maximum efficiency, which cuts the cost of energy and other inputs. GE reports, “In the commercial aviation industry alone, a one percent improvement in fuel savings would yield a savings of $30 billion over 15 years. Likewise, a 1% efficiency improvement in the global gas-fired power plant fleet could yield a $66 billion savings in fuel consumption.”[25]

McKinsey cites the use of data-driven innovation in helping achieve a “50% decrease in product development and assembly cost for manufacturers.”[26] The ability for Big Data to make our products better and cheaper will enable U.S. manufacturers to compete far more successfully in highly price-competitive global markets, where we must vie against competitors from countries with far lower labor and operational costs.

The downstream economic and competitive implications of data-driven productivity are profound. The global demand for the sensing equipment and analytical algorithms needed to produce industrial efficiency is enormous. Further, consider the benefits of lower transportation, shipping, and utility costs on U.S. industrial and residential customers who enjoy a significant portion of the surplus such productivity generates, freeing up resources for use elsewhere in the economy.

Simafore Analytics identified seven areas in which Big Data and the era of sensor and software-based operations and machine learning is transforming manufacturing.[27] These include:

  • Engineering Design – Using historical data to select optimal engineering “parameters, actions, and components.”
  • Manufacturing Systems – Using data-based “machine learning and computational intelligence” for better control of manufacturing systems.
  • Decision Support Systems – Using data-based tools like Neural On-Line Analytical Processing System to coordinate production processes.  
  • Shop Floor Control and Layout – Using "knowledge generated from mining historical work in process data” to optimize floor control and layout.
  • Fault Detection and Quality Improvement – Using Big Data for success, defect, and failure pattern identification.
  • Preventative Maintenance – Using historical data and predictive analytics to maintain systems.
  • Customer relationship management – Using customer demand data to modify product design features to meet the customer’s needs.


Healthcare and Wellness

The healthcare sector generates colossal amounts of data from research and patient care. The agglomeration of digitized genomic and clinical information, together with the proliferation of biosensors and the growth of e-health records and telemedicine, will add substantially to this data flow. This accreting mass of information contains insight from which medical researchers can produce life- and cost-saving, preventative and therapeutic patient care, as well as more efficient healthcare administration.

Dan Foran, head of informatics at the Rutgers Cancer Institute of New Jersey, told Scientific American, “When you go see a physician…you’re relying on his past experience. What we’re doing now is training the computer to look at large cohorts of thousands and hundreds of thousands (of patient data). It’s as if the doctor were making treatment decisions based on the personal experience of hundreds of thousands of patients.”[28]

Beyond better healthcare, there is a matter of cost. Healthcare costs in the United States dwarf those of our competitors and continue to grow at a much faster pace than abroad. Yet, as with other industries, Big Data can be used to find efficiencies and cost savings in how medical products and care are delivered. As such, the competitiveness implications of such savings are staggering. In harnessing the power of Big Data, McKinsey estimates $300 billion in potential value to U.S. healthcare alongside an 8% reduction in costs.[29]

The sharing by drug companies of anonymized clinical trial data is producing fresh insight into pharmaceutical safety and effectiveness. As algorithmic and crowd-sourced analysis of medical trials produce better medicine, the cost of expensive litigation and liability judgments will ease. What is more, data-driven innovation can be applied to the business of healthcare delivery. CIO reports that “a 1% reduction in processing inefficiencies in the global healthcare industry could yield more than $63 billion in healthcare savings.”[30]


Workforce Development and Industry Impact

There are cascading benefits that can be realized across numerous industries. In the same way that exploiting Big Data can yield insight to improve healthcare systems, it can be used to generate competitiveness-enhancing improvements in human capital development. Nothing is as vital to U.S. competitiveness and economic success as a highly skilled workforce able to meet the requirements of a high-tech economy where a mastery of science, technology, engineering and math (STEM) skills is paramount.   

Big Data can be used to understand how people learn and the factors that lead to student failure. This will enable experts to devise more effective teaching and training techniques customized to individuals and micro-segments based on how they learn best. Other industries that can capitalize on the fruits of Big Data include:


A third domain in which data is reshaping America’s competitive landscape is enterprise organization, management, and decision making. Companies involved in high-volume transactions and that operate large databases are exploring how to shift their business model, strategy, and value proposition to capitalize on the marketability of their data. [32] To take full advantage, successful companies are establishing new executive positions, such as Data Officer, Analytics Officer, and Data Scientist.[33]

With Big Data, enterprises can (with greater speed and accuracy) better manage inventories, assets, and logistics, as well as set optimal prices based on the most up-to-date market information. Among the most powerful tools being created are algorithms and predictive models using data to provide foreknowledge. As an example, “one global beverage company integrates daily weather forecast data from an outside partner into its demand and inventory planning process.”[34]

Advanced analytics provide a basis for swift, trustworthy, fact-based decision making, enabling enterprises to stay ahead of high velocity change in markets and the competitive playing field. By collecting data from their business units, enterprises can develop dashboards to monitor and better understand systemic and organizational performance, which can help drive productivity, quality, and profitability. In some cases, data-driven innovation is able to remove the mistake-prone human element through smart systems that auto-decide or self-adjust operations.

Erik Brynjolfsson, director of the MIT Center for Digital Business and a top expert on the effect of IT on productivity reports, notes that “a shift from using intuition toward using data and analytics in making decisions…Specifically, a one-standard-deviation increase toward data and analytics was correlated with about a 5% to 6% percent improvement in productivity and a slightly larger increase in profitability in those same firms.”[35]



As investors, corporate planners, and entrepreneurs make decisions about where to deploy capital, establish business operations, and create jobs, they look carefully at the quality of the business environment they are considering. In today’s global economy, they have many choices as nations compete to offer the most desirable business environment. The factors that make up an attractive business environment include: access to ample customers; reasonable costs; affordable finance; a highly skilled quality workforce; world-class energy and infrastructure; a sound fiscal and monetary system; good governance; and a fertile innovation system.

Big Data and data-driven innovation can be employed to improve America’s performance in each category through what CAP calls an “empirical approach to government.”[36] Bill Bratton, the well-known big city police chief, pioneered the use of Big Data to chart the location and circumstances of violent crime. The insight enabled preventative strategies that made the community safer and businesses more secure. 

Big Data analytics can yield insights that lead to a better understanding of how the economy functions and the likely effects of laws, taxes, regulations, and policies on society and the economy—critically, before they are enacted. Data can also be used to generate more accurate economic data and the effects of economic, fiscal, monetary, and regulatory policies. This comes in addition to: preventing and mitigating threats to public health and national security; improving education systems; offering more efficient public services; and ferreting out fraud, waste, and abuse.



The United States is better positioned than any other country to lead and gain a first mover advantage in the data-driven revolution. It was American innovators who pioneered ICT, creating the Internet, advanced computer science, personal computing, and mobile phones. We remain at the forefront in data-driven architecture, which includes sensor technology, robotics, analytical software, electromagnetic spectrum efficiency, and nanotechnology, to name a few.

More than this historical leadership, America’s innovation system is the world’s most fertile. The country’s firms and institutions hold more patents than those in any other country. The United States continues to hold a decisive global qualitative technological edge. We have the best national labs, technology clusters, innovation hubs, and research institutions. The majority of the world’s top universities are located in the United States.[37] No surprise then that the world’s 10 most innovative companies in Big Data are located here,[38] and some 90% of the top 500 supercomputing systems used around the world are made by U.S. companies.[39]

In their article, “The Coming Tech-led Boom,” authors Mark Mills and Julio Ottino observe that “we sit again on the cusp of three grand technological transformations with the potential to rival that of the past century. All find their epicenters in America: big data, smart manufacturing, and the wireless revolution.”[40]

Among our many advantages, the United States has tremendous cultural and professional diversity, possessing unique perspectives and unparalleled expertise across the sciences and in cross-disciplines, where perhaps the richest analytical discoveries will be found. We offer political stability (relative to other nations), opportunity, and a high quality of life that still attracts the world’s best minds. We enjoy wide freedoms backed up by law, including the liberty to collect, analyze, and use information. We value and foster entrepreneurship. And as good as we are at competing, Americans are equally keen on collaboration, which is a necessity for world-class innovation. 


Despite America’s inherent advantages in data-driven innovation, we must overcome a number of pitfalls, threats, and obstacles to excel in the face of international competition. These include:

Human Capital – One of the reasons for the enormous shortfall detected by McKinsey in the analytical skills of our workforce is that too few of our people are studying and specializing in the STEM disciplines so critical to the Big Data industry.[41] According to standardized international testing, our student body is performing woefully in STEM compared to their peers in other countries.[42]

R&D Investment – We continue to lag behind other nations in public spending on R&D as a percentage of GDP. The lion’s share of federal research funding goes to the life sciences at the expense of critical data-driven initiatives, such as high-performance computing, data modeling, simulation, and analytics. Private sector research is constrained by short-term pressure to meet earnings targets rather than investment in long-term competitiveness.

Fear and Unawareness – Big Data’s potential to improve life can be impeded or even derailed by public apprehensions about privacy, job loss, official ignorance about the opportunities, and/or government mismanagement. We need an enlightened national dialogue on data and innovation to foster a well-informed public and officialdom about the opportunities, stakes, risks, and requirements involved.

Rules of the Road – Every great economic transformation requires modern “rules of the road” to reconcile conflicting interests. There are persistent questions about who owns, secures, and can access data. Industry, consulting with customers and the public, must adopt proper codes of conduct, best practices, and ethical guidelines dealing with data ownership, access, and use to establish trust and legitimacy. Lawmakers and regulators need to be prudent and well-informed to get the rules right.

Privacy and Civil Liberty – The misuse of private data, the breach of personal medical and financial information, and the potential for data-based profiling that might violate individual rights and opportunities are legitimate concerns. Without public trust, the enormous good in Big Data cannot be brought to fruition. Yet, perhaps ironically, it is data-driven innovation that can enhance the technical and procedural means for protecting privacy and civil liberties.  By fostering public trust and showing the world how it’s done, the U.S. business system has the opportunity to make privacy protection a comparative advantage, rather than an impediment to innovation.

Cybersecurity – Part and parcel of data protection is cybersecurity. The Center for Strategic and International Studies says bluntly that the United States is unprepared to defend its computers and networks against myriad cyber threats.[43] McAfee underscores this, reporting that “if there is a race among governments to harden their civilian infrastructure against cyber-attack … Europe and the United States are falling behind Asia.”[44] Cybersecurity will undoubtedly continue to play a role in how much trust the public places in the Big Data revolution or the faith that Big Data companies place in the United States.

Infrastructure – The growth in mobile commerce and the broader use of electromagnetic spectrum for wireless communications will be equally explosive. Improved capacity and efficiency of our infrastructure (such as wired and wireless broadband networks) and the U.S. electric grid must keep pace. No element of the Big Data ecosystem can function in the absence of a reliable and affordable supply of electricity.  Without energy, electronic 0s and 1s can’t exist, much less tell their story. Thus, there’s no overstating the national and corporate competitive advantage in having ample energy delivered on demand via a world-class electric grid. Nor can one overstress the benefits of being the first mover in providing solutions to every need related to the efficient electric generation, distribution, and usage, such as “smart grid” technologies. Despite massive needs, current U.S. infrastructure spending is about the same as it was in 1968, when the country’s economy was much smaller.[45] According to the World Economic Forum, the United States ranks 33rd worldwide in “quality of electricity supply.”[46] In 2012, we ranked 17th in the UN International Telecommunication Union ITC development index.[47]

Trade and International Rules – For the United States to take full competitive advantage of data-driven innovation, we need access to international information flows and to markets abroad for our services. A Progressive Economy report on 21st-century trade policy notes that “no international agreement protects the free flow of data across borders in the way that the GATT system has provided for the free flow of goods.”[48] Coherent national and international norms and rules on data flow, cybersecurity, privacy, trade in services, and IP rights (which are easier to steal in the digital world) are essential.

Governments around the world are attempting to gain greater control over the flow of information to serve political objectives. These efforts take many forms, including: capricious standards and regulations on content, data sharing, and Internet access; arbitrary stipulations on the location of servers and data storage facilities; and anti-competitive controls on the information technology supply chain. Firewalls and disparate national rules governing the Internet will turn the global information superhighway into a balkanized collection of back alleys and barricaded side streets impeding mankind’s progress in harnessing Big Data for good. [J1]


Excess and Irresponsibility – Despite the great potential in Big Data, it must be approached with a sense of humility and deep responsibility. The “garbage in/garbage out” rule can mean that inaccurate, unrepresentative, or improperly analyzed data can result in big mistakes and giant failures.  As the Harvard Business Review notes, no matter how comprehensive or well-analyzed, Big Data needs to be complemented by "big judgment."[49]




Each of the areas discussed above are hurdles to be overcome but also competitive opportunities to meet global needs with our world-leading strategies, policies, practices, technologies, and services. Other countries are embracing Big Data and building strategies to seize the economic high ground. The European Union has embraced the IoE, undertaking an extensive Big Data Public Private Forum and developing strategic research and innovation priorities to capitalize on data-driven innovation.  

Among a nation’s greatest assets for seizing the Big Data future is supercomputing. While this is an area the United States has long led, Europe, Japan, India, and others are investing heavily to catch up—and with the eye to surpass us. They are gaining ground.[50] Not only is Europe working to build better supercomputers, the EU is also striving to provide high-power computing support for small and middle-sized businesses. These are important competitive developments. What’s clear is that leadership in supercomputer infrastructure and access is not some academic luxury but a competitive necessity for the United States.[51]

To be sure, Asia’s massive markets are attracting manufacturing, which in turn attracts innovation. China’s 800 million (and growing) mobile phones and potential Internet connections dwarf the scale possible in the United States. This is an advantage but one that will be greatly diminished as China erects a “great firewall” on its Internet. A similar innovation-dampening approach is being seen in India, Progressive Economy reports, as the country is “requiring telecommunication companies to locate their servers in a country where they can be controlled and hand over data.”[52]

Developing countries are well-positioned to bypass expensive legacy computer and communication systems and jump directly to the state-of-the-art networks that can support new industries and the latest thinking. Again, this is an advantage but one diluted by economic, infrastructure and human resource challenges in developing regions.

The reality is that no nation is better positioned, from top to bottom, than the United States to seize Big Data as a conduit for innovation and global economic competitiveness. Helping the world learn from and make use of the globe’s accreting mass of data is a huge business America is uniquely capable of leading. 

The renowned business guru W. Edwards Deming famously said, “In God we trust. All others bring data.” Bring it we must to renew America’s competitiveness and lead the way into a promising new epoch of human advancement.

John Raidt is vice president of Jones Group International, a Northern Virginia-based consultancy. A former staff director of the U.S. Senate Committee on Commerce, Science, and Transportation, he is a fellow with the Atlantic Council, a scholar with the U.S. Chamber of Commerce Foundation, and the author of American Competitiveness. Prior to his service as deputy to General James Jones, Special Envoy for Middle East Regional Security, he served as a staff member of key national commissions including the 9/11 Commission, the Commission on the National Guard and Reserves, and the Independent Commission on the Security Forces of Iraq.



[1] Arthur Conan Doyle, "The Adventure of the Copper Beeches," The Strand Magazine, 1892.

[2] “Innovate America: National Innovation Initiative Summit and Report,” Council on Competitiveness, 2005, 8.

[3] W. Brian Arthur, “The Second Economy,” McKinsey Quarterly, October 2011.

[4] Peter C. Evans and Marco Annunziatta, “Industrial Internet: Pushing the Boundaries of Minds and Machines,” GE, 26 Nov. 2012, 3. 

[5] Joseph Bradley, Joel Barbier, and Doug Handler, “Embracing the Internet of Everything To Capture Your Share of $14.4 Trillion,” Cisco, 2013, 3.

[6] Thor Olavsrud, “Big Data Will Drive the Industrial Internet,” CIO, 21 June 2013. 

[7] Edward Gresser, “21st Century Trade Policy: The Internet and the Next Generation’s Global Economy,” Progressive Economy, 31 Jan. 2014, 1.

[8] “Better Business Outcomes with IBM Big Data and Analytics,” IBM Software, January 2014, 2.

[9] James Manyika et al., “Big Data: The Next Frontier for Innovation, Competition, and Productivity” McKinsey Global Institute, May 2011, 11.

[10] “Building with Big Data,” The Economist, 26 May 2011.                                                                                                                         

[11] Manyika, “Big Data: The Next Frontier,” 11.

[12] “Building with Big Data,” The Economist.

[13] Srinivasa Rajaram, “Global Markets and Technologies for Sensors,” BCC Research, July 2014.

[14] MarketsandMarkets, "Smart/Intelligent Sensor Market by Type, Technology, Application and by Geography," Forecasts & Analysis to 2013-2020, March 2014.

[15]  “The Market For Robotics Technologies Expected To Surpass $29 Billion By 2018,” BCC Research, 20 Feb. 2013,  

[16] Greg Bensinger, “Before the Drones Come, Amazon Lets Loose the Robots,” Wall Street Journal, 9 Dec. 2013.

[17] TJ McCue, “Cloud Computing: United States Businesses Will Spend $13 Billion On It,” Forbes, 29 Jan. 2014.

[18] Mark P. Mills, “The Next Great Growth Cycle,” The American, 25 Aug. 2012.

[19] Michael Lewis, Moneyball: The Art of Winning an Unfair Game (W. W. Norton & Company, 2004).

[20] Daniel Esty and Reece Rushing, “Governing by the Numbers: The Promise of Data-Driven Policymaking in the Information Age,” Center for American Progress, April 2007, 5.

[21] Manyika, “Big Data: The Next Frontier,” 8.

[22] Ibid., 67.

[23] “Better Business Outcomes,” 5.

[24] Mills, “The Next Great Growth Cycle.”

[25] Evans and Annunziatta, “Industrial Internet.”

[26] Manyika, “Big Data: The Next Frontier,” 8.

[27] Bala Deshpande, "7 Reasons Why Big Data for Manufacturing Analytics is Yesterday’s News," SimaFore Analytics, 9 May 2012.

[28] Neil Savage, “Bioinformatics: Big Data Versus the Big C,” Scientific American, 311 no. 1 (2014): S21.

[29] Manyika, “Big Data: The Next Frontier,” 8.

[30] Olavsrud, “Big Data Will Drive the Industrial Internet.” 

[31] “Building with Big Data,” The Economist.

[32] “Better Business Outcomes,” 8.

[33] Ibid., 3.

[34] Brad Brown et al., “Are You Ready for the Era of ‘Big Data’?” McKinsey Quarterly, October 2011.

[35] Erik Brynjolfsson, Jeff Hammerbacher, and Brad Stevens, “Competing Through data: Three Experts Offer Their Game Plans,” McKinsey Quarterly, October 2011.

[36] Esty and Rushing, “Governing by the Numbers.”

[37] Mark Mills and Julio Ottino, “The Coming Tech-led Boom,” Wall Street Journal, 30 Jan. 2012.

[38] "The World's Top 10 Most Innovative Companies in Big Data," Fast Company, 10 Feb. 2014, <> (18 Aug. 2014).

[39] Patrick Thibodeau, "China has the Fastest Supercomputer, but the U.S. Still Rules," Computerworld, 2 July 2014.

[40] Mills and Ottino, “The Coming Tech Led Boom.”

[41] Manyika, “Big Data: The Next Frontier,” 105.

[42] “Compete: New Challenges, New Answers,” Council On Competitiveness, November 2008, 5. 

[43]  "US Lacks People, Authorities to Face Cyber Attack," Associated Press, 16 Mar. 2011.

[44] Stewart Baker and Natalia Filipiak, “In the Dark: Crucial Industries Confront Cyberattacks,” McAfee Second Annual Critical Infrastructure Protection Report, 2011, 2.

[45] According to the CBO’s estimates, if historical spending and revenue patterns continue in the future, the highway account of the trust fund would be unable to meet its obligations sometime during FY 2012. Similarly, for the 2011-2021 period, outlays would exceed revenues and interest credited to the fund by about $120 billion. See, Douglas Elmendorf, “Spending and Funding for Highways,” Economic and Budget Issue Brief, (Washington, DC: Congressional Budget Office, 2011), 6.

[46] Lucas Kawa, "America's Infrastructure Ranks... 25th In The World," Business Insider, 16 Jan. 2013.

[47] "Measuring the Information Society," International Telecommunication Union, 2013, 54.

[48] GATT is the acronym for the General Agreement on Tariffs and Trade, an international agreement that seeks to reduce tariffs and trade barriers to promote international trade and prosperity. See, Gresser, “21st Century Trade Policy.”

[49]  Andrew McAfee, "Big Data’s Biggest Challenge? Convincing People NOT to Trust Their Judgment," Harvard Business Review, 9 Dec. 2013.

[50] David F. McQueeney, Statement to U.S. House Subcommittee on Technology and Subcommittee on Research, "Next Generation Computing and Big Data Analytics," Joint hearing, April 24, 2013.

[51] McQueeney, “Next Generation Computing.”

[52] Gresser, “21st Century Trade Policy.”